Title :
Adaptive neural control for a class of stochastic nonlinear pure-feedback systems with unknown control direction
Author :
Yu Zhaoxu ; Luo Jianxu ; Du Hongbin
Author_Institution :
Dept. of Autom., East China Univ. of Sci. & Technol., Shanghai, China
Abstract :
This paper addresses a class of uncertain stochastic nonlinear pure-feedback systems with unknown control direction. With using the decoupled backstepping technique, adaptive neural control schemes are designed to solve the stabilization problem of such systems. Stability analysis is presented to guarantee that all the error variables are semi-globally ultimately bounded with desired probability in a compact set. The effectiveness of the proposed design is verified by simulation results.
Keywords :
adaptive control; control system synthesis; feedback; neurocontrollers; nonlinear systems; stability; stochastic systems; uncertain systems; adaptive neural control; compact set; decoupled backstepping technique; stability analysis; stabilization problem; uncertain stochastic nonlinear pure-feedback system; unknown control direction; Adaptive systems; Artificial neural networks; Backstepping; Control design; Nonlinear systems; Stability analysis; Adaptive Control; Backstepping; Neural Networks (NN); Nussbaum Gain Functions (NGFs); Stochastic Pure-Feedback Systems;
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768
